Large Language Model Algorithm Engineer
5 days ago
DepartmentEngineering and Technology- LevelExperienced (Individual Contributor)- LocationSingaporeThe Engineering and Technology team is at the core of the Shopee platform development. The team is made up of a group of passionate engineers from all over the world, striving to build the best systems with the most suitable technologies. Our engineers do not merely solve problems at hand; We build foundations for a long-lasting future. We don't limit ourselves on what we can or can't do; we take matters into our own hands even if it means drilling down to the bottom layer of the computing platform. Shopee's hyper-growing business scale has transformed most "innocent" problems into huge technical challenges, and there is no better place to experience it first-hand if you love technologies as much as we do. **About the Team**: **The Shopee Large Language Model team(LLM team) is committed to building the leading multi-lingual large model in Southeast Asia, building a complete Model-as-a-Infrastructure product support system, and supporting the intelligent upgrade and transformation of the company's business.** - ** Exploration and implementation of the core algorithms of large language models, including ultra-large-scale pre-training, instruction fine-tuning, reinforcement learning, etc., from a multilingual perspective to solve problems such as hallucinations and long texts etc**: - ** Optimize the inference speed of language models, explore and implement acceleration strategies such as Medusa, Speculative Decoding, multi-LoRA inference, and Pruning, and build an inference framework for LLMs.**: - ** Establish a complete large model evaluation system, provide standardized model evaluation capabilities, establish and improve evaluation data sets, and use model evaluation to reversely drive and improve the performance of large language models in actual business.**: - ** Data algorithm of Large language model involving construction of multi-language pre-training, instruction fine-tuning, human preference behavior and other data systems, establishing a complete engineering system for model fine-tuning and data set preparation, effectively improving data set quality and delivery capabilities.** **Requirements**: - ** Excellent coding skills, data structure and basic algorithm skills, proficiency in Python/Pytorch coding, and harness the Hands-on ability.**: - ** Those who are familiar with NLP and CV related algorithms and technologies, and those who are familiar with large model training and RL algorithms are preferred;**: - ** Familiar with the basic principles and training methods of industry-leading LLM (such as GPT, LLaMA), or familiar with the basic principles and training methods of mainstream multi-modal large models (such as Flamingo, LLaVA), and have research experience in text generation or dialogue systems, etc.**: - ** Good communication and collaboration skills, able to explore new technologies with the team and promote technological progress.
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